Disclaimer: These are my notes of the course “Getting and cleaning data” from the Data Science Specialization offered by Johns Hopkins University in Coursera. These notes are based on the Jeff Leek videos from that course.
As we will be analyzing data, we will first consider the process of getting and cleaning data using R.
The four things you should have.
According to Wikipedia, “data are values of qualitative or quantitative variables, belonging to a set of items”.
Raw data is the original source of data, and it is often hard to use as it is for data analyses and have to be processed (which is part of the data analysis). The processed data is ready for the analysis, and it includes merging, sub-setting, transforming, etc. Please take into account that all steps should be documented.
Once the raw data is processed we will have tidy data.
Checking and creating directories: an example of how to check if a directory already exists and to create one is given in the following chunk of code:
if(!file.exists("ExampleofCreatingFile")){
dir.create("ExampleofCreatingFile")
}Getting data from the internet can be done using the
download.file() function.
# fileURL <- "https://www.stats.govt.nz/assets/Uploads/Effects-of-COVID-19-on-trade/Effects-of-COVID-19-on-trade-At-15-December-2021-provisional/Download-data/effects-of-covid-19-on-trade-at-15-december-2021-provisional.csv"
# download.file(url = fileURL, destfile = ".\\ExampleofCreatingFile\\COVID.csv")
# list.files(".\\ExampleofCreatingFile")This can be done using the read.table() function.
Warning! as it reads the data into RAM, therefore
big data can cause problems.
COVID <- read.table(".\\ExampleofCreatingFile\\COVID.csv", sep = ",", header = TRUE, na.string = "")
Camera <- read.csv(".\\ExampleofCreatingFile\\Fixed_Speed_Cameras.csv")
head(COVID)## Direction Year Date Weekday Country Commodity Transport_Mode Measure
## 1 Exports 2015 01/01/2015 Thursday All All All $
## 2 Exports 2015 02/01/2015 Friday All All All $
## 3 Exports 2015 03/01/2015 Saturday All All All $
## 4 Exports 2015 04/01/2015 Sunday All All All $
## 5 Exports 2015 05/01/2015 Monday All All All $
## 6 Exports 2015 06/01/2015 Tuesday All All All $
## Value Cumulative
## 1 104000000 1.04e+08
## 2 96000000 2.00e+08
## 3 61000000 2.62e+08
## 4 74000000 3.36e+08
## 5 105000000 4.42e+08
## 6 76000000 5.18e+08head(Camera)## ï..X Y fid objectid status arc_street gis_id camtype camid uid_no
## 1 -8529792 4767599 1 1 5140 Portable 0
## 2 -8529392 4769667 2 2 5141 Portable 0
## 3 -8529325 4769664 3 3 5142 Portable 0
## 4 -8536905 4773779 4 4 5143 Portable 0
## 5 -8536828 4773768 5 5 5144 Portable 0
## 6 -8539241 4763528 6 6 5145 Portable 0
## siteno quadrant disttno yrmnth location city
## 1 0 2 12 0 500 blk West 28th Street EB Baltimore
## 2 0 2 14 0 100 Blk W. University Parkway EB Baltimore
## 3 0 2 14 0 100 Blk W. University Parkway WB Baltimore
## 4 0 2 5 0 6100 blk Cross Country Blvd EB Baltimore
## 5 0 2 5 0 6100 blk Cross Country Blvd WB Baltimore
## 6 0 3 8 0 5100 blk Baltimore National Pike EB Baltimore
## status_1 logno hprtlocati site_vst_d comappdate
## 1 Final
## 2 Final
## 3 Final
## 4 Final
## 5 Final
## 6 Final
## schllocati vendname n_site_id depl_id post_spd
## 1 Career Academy NA 0
## 2 Hampden Elementary / Middle School NA 0
## 3 Hampden Elementary / Middle School NA 0
## 4 Cross Country Elementary / Middle School NA 0
## 5 Cross Country Elementary / Middle School NA 0
## 6 North Bend Elementary / Middle School NA 0
## tigr_spd batry_mont lanes dplmt_dat map_final contact
## 1 0 NA 0 Phillip Mellerson
## 2 0 NA 0 Phillip Mellerson
## 3 0 NA 0 Phillip Mellerson
## 4 0 NA 0 Phillip Mellerson
## 5 0 NA 0 Phillip Mellerson
## 6 0 NA 0 Phillip Mellerson
## email f2ndemail
## 1 phillip.mellerson@baltimorecity.gov kiesham.brice@baltimorecity.gov
## 2 phillip.mellerson@baltimorecity.gov kiesham.brice@baltimorecity.gov
## 3 phillip.mellerson@baltimorecity.gov kiesham.brice@baltimorecity.gov
## 4 phillip.mellerson@baltimorecity.gov kiesham.brice@baltimorecity.gov
## 5 phillip.mellerson@baltimorecity.gov kiesham.brice@baltimorecity.gov
## 6 phillip.mellerson@baltimorecity.gov kiesham.brice@baltimorecity.gov
## editedby
## 1 Jason Chang
## 2 Jason Chang
## 3 Jason Chang
## 4 Jason Chang
## 5 Jason Chang
## 6 Jason Changlibrary(xlsx)## Warning: package 'xlsx' was built under R version 3.6.3Irisdata <- read.xlsx(".\\ExampleofCreatingFile\\IrisSetosaCompleto.xlsx", sheetIndex = 1, header = TRUE)
head(Irisdata)## Largo.Sépalo Ancho.sépalo Largo.pétalo Ancho.pétalo Especie
## 1 5.1 3.5 1.4 0.2 Iris-setosa
## 2 4.9 3.0 1.4 0.2 Iris-setosa
## 3 4.7 3.2 1.3 0.2 Iris-setosa
## 4 4.6 3.1 1.5 0.2 Iris-setosa
## 5 5.0 3.6 1.4 0.2 Iris-setosa
## 6 5.4 3.9 1.7 0.4 Iris-setosa## Subsetting
IrisdataSubset <- read.xlsx(".\\ExampleofCreatingFile\\IrisSetosaCompleto.xlsx", sheetIndex = 1, colIndex = 3:5, rowIndex = 1:10)
head(IrisdataSubset)## Largo.pétalo Ancho.pétalo Especie
## 1 1.4 0.2 Iris-setosa
## 2 1.4 0.2 Iris-setosa
## 3 1.3 0.2 Iris-setosa
## 4 1.5 0.2 Iris-setosa
## 5 1.4 0.2 Iris-setosa
## 6 1.7 0.4 Iris-setosaXML stands for Extensible Markup Language and it is used to store structured data. I DID NOT FIND ANY REFERENCE TO AN EASY WAY TO MAKE THIS WORK.
library(RCurl)## Warning: package 'RCurl' was built under R version 3.6.3library(XML)## Warning: package 'XML' was built under R version 3.6.3fileName <- system.file("exampleData", "mtcars.xml", package="XML")
doc <- xmlParse(fileName,useInternal = TRUE)
rootNode <- xmlRoot(doc)
xmlName(rootNode)## [1] "dataset"names(rootNode)## variables record record record record record
## "variables" "record" "record" "record" "record" "record"
## record record record record record record
## "record" "record" "record" "record" "record" "record"
## record record record record record record
## "record" "record" "record" "record" "record" "record"
## record record record record record record
## "record" "record" "record" "record" "record" "record"
## record record record record record record
## "record" "record" "record" "record" "record" "record"
## record record record
## "record" "record" "record"rootNode[[1]]## <variables count="11">
## <variable unit="Miles/gallon">mpg</variable>
## <variable>cyl</variable>
## <variable>disp</variable>
## <variable>hp</variable>
## <variable>drat</variable>
## <variable>wt</variable>
## <variable>qsec</variable>
## <variable>vs</variable>
## <variable type="FactorVariable" levels="automatic,manual">am</variable>
## <variable>gear</variable>
## <variable>carb</variable>
## </variables>rootNode[[1]][[1]]## <variable unit="Miles/gallon">mpg</variable>xmlSApply(rootNode,xmlValue)## variables
## "mpgcyldisphpdratwtqsecvsamgearcarb"
## record
## " 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4"
## record
## " 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4"
## record
## " 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1"
## record
## " 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1"
## record
## " 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2"
## record
## " 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1"
## record
## " 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4"
## record
## " 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2"
## record
## " 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2"
## record
## " 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4"
## record
## " 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4"
## record
## " 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3"
## record
## " 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3"
## record
## " 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3"
## record
## " 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4"
## record
## " 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4"
## record
## " 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4"
## record
## " 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1"
## record
## " 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2"
## record
## " 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1"
## record
## " 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1"
## record
## " 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2"
## record
## " 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2"
## record
## " 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4"
## record
## " 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2"
## record
## " 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1"
## record
## " 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2"
## record
## " 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2"
## record
## " 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4"
## record
## " 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6"
## record
## " 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8"
## record
## " 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2"xpathSApply(rootNode, "//variables",xmlValue)## [1] "mpgcyldisphpdratwtqsecvsamgearcarb"JSON stands for JavaScript Object Notation.
library(jsonlite)## Warning: package 'jsonlite' was built under R version 3.6.3jsonData <- fromJSON("https://api.github.com/users/jtleek/repos")
names(jsonData)## [1] "id" "node_id"
## [3] "name" "full_name"
## [5] "private" "owner"
## [7] "html_url" "description"
## [9] "fork" "url"
## [11] "forks_url" "keys_url"
## [13] "collaborators_url" "teams_url"
## [15] "hooks_url" "issue_events_url"
## [17] "events_url" "assignees_url"
## [19] "branches_url" "tags_url"
## [21] "blobs_url" "git_tags_url"
## [23] "git_refs_url" "trees_url"
## [25] "statuses_url" "languages_url"
## [27] "stargazers_url" "contributors_url"
## [29] "subscribers_url" "subscription_url"
## [31] "commits_url" "git_commits_url"
## [33] "comments_url" "issue_comment_url"
## [35] "contents_url" "compare_url"
## [37] "merges_url" "archive_url"
## [39] "downloads_url" "issues_url"
## [41] "pulls_url" "milestones_url"
## [43] "notifications_url" "labels_url"
## [45] "releases_url" "deployments_url"
## [47] "created_at" "updated_at"
## [49] "pushed_at" "git_url"
## [51] "ssh_url" "clone_url"
## [53] "svn_url" "homepage"
## [55] "size" "stargazers_count"
## [57] "watchers_count" "language"
## [59] "has_issues" "has_projects"
## [61] "has_downloads" "has_wiki"
## [63] "has_pages" "has_discussions"
## [65] "forks_count" "mirror_url"
## [67] "archived" "disabled"
## [69] "open_issues_count" "license"
## [71] "allow_forking" "is_template"
## [73] "web_commit_signoff_required" "topics"
## [75] "visibility" "forks"
## [77] "open_issues" "watchers"
## [79] "default_branch"names(jsonData$owner)## [1] "login" "id" "node_id"
## [4] "avatar_url" "gravatar_id" "url"
## [7] "html_url" "followers_url" "following_url"
## [10] "gists_url" "starred_url" "subscriptions_url"
## [13] "organizations_url" "repos_url" "events_url"
## [16] "received_events_url" "type" "site_admin"jsonData$owner$login## [1] "jtleek" "jtleek" "jtleek" "jtleek" "jtleek" "jtleek" "jtleek" "jtleek"
## [9] "jtleek" "jtleek" "jtleek" "jtleek" "jtleek" "jtleek" "jtleek" "jtleek"
## [17] "jtleek" "jtleek" "jtleek" "jtleek" "jtleek" "jtleek" "jtleek" "jtleek"
## [25] "jtleek" "jtleek" "jtleek" "jtleek" "jtleek" "jtleek"Convert to JSON data
myjson <- toJSON(iris, pretty = TRUE)
cat(myjson)## [
## {
## "Sepal.Length": 5.1,
## "Sepal.Width": 3.5,
## "Petal.Length": 1.4,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.9,
## "Sepal.Width": 3,
## "Petal.Length": 1.4,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.7,
## "Sepal.Width": 3.2,
## "Petal.Length": 1.3,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.6,
## "Sepal.Width": 3.1,
## "Petal.Length": 1.5,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5,
## "Sepal.Width": 3.6,
## "Petal.Length": 1.4,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.4,
## "Sepal.Width": 3.9,
## "Petal.Length": 1.7,
## "Petal.Width": 0.4,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.6,
## "Sepal.Width": 3.4,
## "Petal.Length": 1.4,
## "Petal.Width": 0.3,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5,
## "Sepal.Width": 3.4,
## "Petal.Length": 1.5,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.4,
## "Sepal.Width": 2.9,
## "Petal.Length": 1.4,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.9,
## "Sepal.Width": 3.1,
## "Petal.Length": 1.5,
## "Petal.Width": 0.1,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.4,
## "Sepal.Width": 3.7,
## "Petal.Length": 1.5,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.8,
## "Sepal.Width": 3.4,
## "Petal.Length": 1.6,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.8,
## "Sepal.Width": 3,
## "Petal.Length": 1.4,
## "Petal.Width": 0.1,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.3,
## "Sepal.Width": 3,
## "Petal.Length": 1.1,
## "Petal.Width": 0.1,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.8,
## "Sepal.Width": 4,
## "Petal.Length": 1.2,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.7,
## "Sepal.Width": 4.4,
## "Petal.Length": 1.5,
## "Petal.Width": 0.4,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.4,
## "Sepal.Width": 3.9,
## "Petal.Length": 1.3,
## "Petal.Width": 0.4,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.1,
## "Sepal.Width": 3.5,
## "Petal.Length": 1.4,
## "Petal.Width": 0.3,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.7,
## "Sepal.Width": 3.8,
## "Petal.Length": 1.7,
## "Petal.Width": 0.3,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.1,
## "Sepal.Width": 3.8,
## "Petal.Length": 1.5,
## "Petal.Width": 0.3,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.4,
## "Sepal.Width": 3.4,
## "Petal.Length": 1.7,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.1,
## "Sepal.Width": 3.7,
## "Petal.Length": 1.5,
## "Petal.Width": 0.4,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.6,
## "Sepal.Width": 3.6,
## "Petal.Length": 1,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.1,
## "Sepal.Width": 3.3,
## "Petal.Length": 1.7,
## "Petal.Width": 0.5,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.8,
## "Sepal.Width": 3.4,
## "Petal.Length": 1.9,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5,
## "Sepal.Width": 3,
## "Petal.Length": 1.6,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5,
## "Sepal.Width": 3.4,
## "Petal.Length": 1.6,
## "Petal.Width": 0.4,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.2,
## "Sepal.Width": 3.5,
## "Petal.Length": 1.5,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.2,
## "Sepal.Width": 3.4,
## "Petal.Length": 1.4,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.7,
## "Sepal.Width": 3.2,
## "Petal.Length": 1.6,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.8,
## "Sepal.Width": 3.1,
## "Petal.Length": 1.6,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.4,
## "Sepal.Width": 3.4,
## "Petal.Length": 1.5,
## "Petal.Width": 0.4,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.2,
## "Sepal.Width": 4.1,
## "Petal.Length": 1.5,
## "Petal.Width": 0.1,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.5,
## "Sepal.Width": 4.2,
## "Petal.Length": 1.4,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.9,
## "Sepal.Width": 3.1,
## "Petal.Length": 1.5,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5,
## "Sepal.Width": 3.2,
## "Petal.Length": 1.2,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.5,
## "Sepal.Width": 3.5,
## "Petal.Length": 1.3,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.9,
## "Sepal.Width": 3.6,
## "Petal.Length": 1.4,
## "Petal.Width": 0.1,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.4,
## "Sepal.Width": 3,
## "Petal.Length": 1.3,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.1,
## "Sepal.Width": 3.4,
## "Petal.Length": 1.5,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5,
## "Sepal.Width": 3.5,
## "Petal.Length": 1.3,
## "Petal.Width": 0.3,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.5,
## "Sepal.Width": 2.3,
## "Petal.Length": 1.3,
## "Petal.Width": 0.3,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.4,
## "Sepal.Width": 3.2,
## "Petal.Length": 1.3,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5,
## "Sepal.Width": 3.5,
## "Petal.Length": 1.6,
## "Petal.Width": 0.6,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.1,
## "Sepal.Width": 3.8,
## "Petal.Length": 1.9,
## "Petal.Width": 0.4,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.8,
## "Sepal.Width": 3,
## "Petal.Length": 1.4,
## "Petal.Width": 0.3,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.1,
## "Sepal.Width": 3.8,
## "Petal.Length": 1.6,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 4.6,
## "Sepal.Width": 3.2,
## "Petal.Length": 1.4,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5.3,
## "Sepal.Width": 3.7,
## "Petal.Length": 1.5,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 5,
## "Sepal.Width": 3.3,
## "Petal.Length": 1.4,
## "Petal.Width": 0.2,
## "Species": "setosa"
## },
## {
## "Sepal.Length": 7,
## "Sepal.Width": 3.2,
## "Petal.Length": 4.7,
## "Petal.Width": 1.4,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.4,
## "Sepal.Width": 3.2,
## "Petal.Length": 4.5,
## "Petal.Width": 1.5,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.9,
## "Sepal.Width": 3.1,
## "Petal.Length": 4.9,
## "Petal.Width": 1.5,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.5,
## "Sepal.Width": 2.3,
## "Petal.Length": 4,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.5,
## "Sepal.Width": 2.8,
## "Petal.Length": 4.6,
## "Petal.Width": 1.5,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.7,
## "Sepal.Width": 2.8,
## "Petal.Length": 4.5,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.3,
## "Sepal.Width": 3.3,
## "Petal.Length": 4.7,
## "Petal.Width": 1.6,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 4.9,
## "Sepal.Width": 2.4,
## "Petal.Length": 3.3,
## "Petal.Width": 1,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.6,
## "Sepal.Width": 2.9,
## "Petal.Length": 4.6,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.2,
## "Sepal.Width": 2.7,
## "Petal.Length": 3.9,
## "Petal.Width": 1.4,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5,
## "Sepal.Width": 2,
## "Petal.Length": 3.5,
## "Petal.Width": 1,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.9,
## "Sepal.Width": 3,
## "Petal.Length": 4.2,
## "Petal.Width": 1.5,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6,
## "Sepal.Width": 2.2,
## "Petal.Length": 4,
## "Petal.Width": 1,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.1,
## "Sepal.Width": 2.9,
## "Petal.Length": 4.7,
## "Petal.Width": 1.4,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.6,
## "Sepal.Width": 2.9,
## "Petal.Length": 3.6,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.7,
## "Sepal.Width": 3.1,
## "Petal.Length": 4.4,
## "Petal.Width": 1.4,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.6,
## "Sepal.Width": 3,
## "Petal.Length": 4.5,
## "Petal.Width": 1.5,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.8,
## "Sepal.Width": 2.7,
## "Petal.Length": 4.1,
## "Petal.Width": 1,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.2,
## "Sepal.Width": 2.2,
## "Petal.Length": 4.5,
## "Petal.Width": 1.5,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.6,
## "Sepal.Width": 2.5,
## "Petal.Length": 3.9,
## "Petal.Width": 1.1,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.9,
## "Sepal.Width": 3.2,
## "Petal.Length": 4.8,
## "Petal.Width": 1.8,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.1,
## "Sepal.Width": 2.8,
## "Petal.Length": 4,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.3,
## "Sepal.Width": 2.5,
## "Petal.Length": 4.9,
## "Petal.Width": 1.5,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.1,
## "Sepal.Width": 2.8,
## "Petal.Length": 4.7,
## "Petal.Width": 1.2,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.4,
## "Sepal.Width": 2.9,
## "Petal.Length": 4.3,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.6,
## "Sepal.Width": 3,
## "Petal.Length": 4.4,
## "Petal.Width": 1.4,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.8,
## "Sepal.Width": 2.8,
## "Petal.Length": 4.8,
## "Petal.Width": 1.4,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.7,
## "Sepal.Width": 3,
## "Petal.Length": 5,
## "Petal.Width": 1.7,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6,
## "Sepal.Width": 2.9,
## "Petal.Length": 4.5,
## "Petal.Width": 1.5,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.7,
## "Sepal.Width": 2.6,
## "Petal.Length": 3.5,
## "Petal.Width": 1,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.5,
## "Sepal.Width": 2.4,
## "Petal.Length": 3.8,
## "Petal.Width": 1.1,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.5,
## "Sepal.Width": 2.4,
## "Petal.Length": 3.7,
## "Petal.Width": 1,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.8,
## "Sepal.Width": 2.7,
## "Petal.Length": 3.9,
## "Petal.Width": 1.2,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6,
## "Sepal.Width": 2.7,
## "Petal.Length": 5.1,
## "Petal.Width": 1.6,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.4,
## "Sepal.Width": 3,
## "Petal.Length": 4.5,
## "Petal.Width": 1.5,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6,
## "Sepal.Width": 3.4,
## "Petal.Length": 4.5,
## "Petal.Width": 1.6,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.7,
## "Sepal.Width": 3.1,
## "Petal.Length": 4.7,
## "Petal.Width": 1.5,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.3,
## "Sepal.Width": 2.3,
## "Petal.Length": 4.4,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.6,
## "Sepal.Width": 3,
## "Petal.Length": 4.1,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.5,
## "Sepal.Width": 2.5,
## "Petal.Length": 4,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.5,
## "Sepal.Width": 2.6,
## "Petal.Length": 4.4,
## "Petal.Width": 1.2,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.1,
## "Sepal.Width": 3,
## "Petal.Length": 4.6,
## "Petal.Width": 1.4,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.8,
## "Sepal.Width": 2.6,
## "Petal.Length": 4,
## "Petal.Width": 1.2,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5,
## "Sepal.Width": 2.3,
## "Petal.Length": 3.3,
## "Petal.Width": 1,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.6,
## "Sepal.Width": 2.7,
## "Petal.Length": 4.2,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.7,
## "Sepal.Width": 3,
## "Petal.Length": 4.2,
## "Petal.Width": 1.2,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.7,
## "Sepal.Width": 2.9,
## "Petal.Length": 4.2,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.2,
## "Sepal.Width": 2.9,
## "Petal.Length": 4.3,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.1,
## "Sepal.Width": 2.5,
## "Petal.Length": 3,
## "Petal.Width": 1.1,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 5.7,
## "Sepal.Width": 2.8,
## "Petal.Length": 4.1,
## "Petal.Width": 1.3,
## "Species": "versicolor"
## },
## {
## "Sepal.Length": 6.3,
## "Sepal.Width": 3.3,
## "Petal.Length": 6,
## "Petal.Width": 2.5,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 5.8,
## "Sepal.Width": 2.7,
## "Petal.Length": 5.1,
## "Petal.Width": 1.9,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.1,
## "Sepal.Width": 3,
## "Petal.Length": 5.9,
## "Petal.Width": 2.1,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.3,
## "Sepal.Width": 2.9,
## "Petal.Length": 5.6,
## "Petal.Width": 1.8,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.5,
## "Sepal.Width": 3,
## "Petal.Length": 5.8,
## "Petal.Width": 2.2,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.6,
## "Sepal.Width": 3,
## "Petal.Length": 6.6,
## "Petal.Width": 2.1,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 4.9,
## "Sepal.Width": 2.5,
## "Petal.Length": 4.5,
## "Petal.Width": 1.7,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.3,
## "Sepal.Width": 2.9,
## "Petal.Length": 6.3,
## "Petal.Width": 1.8,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.7,
## "Sepal.Width": 2.5,
## "Petal.Length": 5.8,
## "Petal.Width": 1.8,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.2,
## "Sepal.Width": 3.6,
## "Petal.Length": 6.1,
## "Petal.Width": 2.5,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.5,
## "Sepal.Width": 3.2,
## "Petal.Length": 5.1,
## "Petal.Width": 2,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.4,
## "Sepal.Width": 2.7,
## "Petal.Length": 5.3,
## "Petal.Width": 1.9,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.8,
## "Sepal.Width": 3,
## "Petal.Length": 5.5,
## "Petal.Width": 2.1,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 5.7,
## "Sepal.Width": 2.5,
## "Petal.Length": 5,
## "Petal.Width": 2,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 5.8,
## "Sepal.Width": 2.8,
## "Petal.Length": 5.1,
## "Petal.Width": 2.4,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.4,
## "Sepal.Width": 3.2,
## "Petal.Length": 5.3,
## "Petal.Width": 2.3,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.5,
## "Sepal.Width": 3,
## "Petal.Length": 5.5,
## "Petal.Width": 1.8,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.7,
## "Sepal.Width": 3.8,
## "Petal.Length": 6.7,
## "Petal.Width": 2.2,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.7,
## "Sepal.Width": 2.6,
## "Petal.Length": 6.9,
## "Petal.Width": 2.3,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6,
## "Sepal.Width": 2.2,
## "Petal.Length": 5,
## "Petal.Width": 1.5,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.9,
## "Sepal.Width": 3.2,
## "Petal.Length": 5.7,
## "Petal.Width": 2.3,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 5.6,
## "Sepal.Width": 2.8,
## "Petal.Length": 4.9,
## "Petal.Width": 2,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.7,
## "Sepal.Width": 2.8,
## "Petal.Length": 6.7,
## "Petal.Width": 2,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.3,
## "Sepal.Width": 2.7,
## "Petal.Length": 4.9,
## "Petal.Width": 1.8,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.7,
## "Sepal.Width": 3.3,
## "Petal.Length": 5.7,
## "Petal.Width": 2.1,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.2,
## "Sepal.Width": 3.2,
## "Petal.Length": 6,
## "Petal.Width": 1.8,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.2,
## "Sepal.Width": 2.8,
## "Petal.Length": 4.8,
## "Petal.Width": 1.8,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.1,
## "Sepal.Width": 3,
## "Petal.Length": 4.9,
## "Petal.Width": 1.8,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.4,
## "Sepal.Width": 2.8,
## "Petal.Length": 5.6,
## "Petal.Width": 2.1,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.2,
## "Sepal.Width": 3,
## "Petal.Length": 5.8,
## "Petal.Width": 1.6,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.4,
## "Sepal.Width": 2.8,
## "Petal.Length": 6.1,
## "Petal.Width": 1.9,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.9,
## "Sepal.Width": 3.8,
## "Petal.Length": 6.4,
## "Petal.Width": 2,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.4,
## "Sepal.Width": 2.8,
## "Petal.Length": 5.6,
## "Petal.Width": 2.2,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.3,
## "Sepal.Width": 2.8,
## "Petal.Length": 5.1,
## "Petal.Width": 1.5,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.1,
## "Sepal.Width": 2.6,
## "Petal.Length": 5.6,
## "Petal.Width": 1.4,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 7.7,
## "Sepal.Width": 3,
## "Petal.Length": 6.1,
## "Petal.Width": 2.3,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.3,
## "Sepal.Width": 3.4,
## "Petal.Length": 5.6,
## "Petal.Width": 2.4,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.4,
## "Sepal.Width": 3.1,
## "Petal.Length": 5.5,
## "Petal.Width": 1.8,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6,
## "Sepal.Width": 3,
## "Petal.Length": 4.8,
## "Petal.Width": 1.8,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.9,
## "Sepal.Width": 3.1,
## "Petal.Length": 5.4,
## "Petal.Width": 2.1,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.7,
## "Sepal.Width": 3.1,
## "Petal.Length": 5.6,
## "Petal.Width": 2.4,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.9,
## "Sepal.Width": 3.1,
## "Petal.Length": 5.1,
## "Petal.Width": 2.3,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 5.8,
## "Sepal.Width": 2.7,
## "Petal.Length": 5.1,
## "Petal.Width": 1.9,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.8,
## "Sepal.Width": 3.2,
## "Petal.Length": 5.9,
## "Petal.Width": 2.3,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.7,
## "Sepal.Width": 3.3,
## "Petal.Length": 5.7,
## "Petal.Width": 2.5,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.7,
## "Sepal.Width": 3,
## "Petal.Length": 5.2,
## "Petal.Width": 2.3,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.3,
## "Sepal.Width": 2.5,
## "Petal.Length": 5,
## "Petal.Width": 1.9,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.5,
## "Sepal.Width": 3,
## "Petal.Length": 5.2,
## "Petal.Width": 2,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 6.2,
## "Sepal.Width": 3.4,
## "Petal.Length": 5.4,
## "Petal.Width": 2.3,
## "Species": "virginica"
## },
## {
## "Sepal.Length": 5.9,
## "Sepal.Width": 3,
## "Petal.Length": 5.1,
## "Petal.Width": 1.8,
## "Species": "virginica"
## }
## ]iris2<- fromJSON(myjson)
head(iris2)## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosaThe function data.table() is written in C, so it is much
faster, for instance, at subsetting, group and updating.
library(data.table)## Warning: package 'data.table' was built under R version 3.6.3DF <- data.frame(x = rnorm(9), y = rep(c("a","b","c"),each = 3), z = rnorm(9))
head(DF,5)## x y z
## 1 -1.7978985 a 0.1156112
## 2 0.4980916 a -0.5277147
## 3 -0.4097869 a -0.1298059
## 4 -0.9060761 b 0.4030851
## 5 -0.9086137 b -1.0879779DT <-data.table(x = rnorm(9), y = rep(c("a","b","c"),each = 3), z = rnorm(9))
head(DT,5)## x y z
## 1: -0.1386099 a -0.7537332
## 2: 1.4045568 a -0.5424090
## 3: -1.2711654 a 1.3848216
## 4: 0.9479388 b 0.2464019
## 5: 0.4464590 b 1.9812184tables()## NAME NROW NCOL MB COLS KEY
## 1: DT 9 3 0 x,y,z
## Total: 0MB# Subsetting rows
DT[2,]## x y z
## 1: 1.404557 a -0.542409DT[DT$y=="a",]## x y z
## 1: -0.1386099 a -0.7537332
## 2: 1.4045568 a -0.5424090
## 3: -1.2711654 a 1.3848216DT[c(2,3)] # It takes 2nd and 3rd rows of DT.## x y z
## 1: 1.404557 a -0.542409
## 2: -1.271165 a 1.384822# Subsetting by columns
DT[, list(mean(x), sum(z))]## V1 V2
## 1: 0.203904 1.701111DT[,table(y)]## y
## a b c
## 3 3 3We can add new columns easily
DT[,w:=z^2]
DT## x y z w
## 1: -0.1386099 a -0.7537332 0.56811370
## 2: 1.4045568 a -0.5424090 0.29420755
## 3: -1.2711654 a 1.3848216 1.91773090
## 4: 0.9479388 b 0.2464019 0.06071388
## 5: 0.4464590 b 1.9812184 3.92522635
## 6: -0.5842602 b -0.1435037 0.02059332
## 7: 0.3548485 c -0.1427674 0.02038253
## 8: -0.2297939 c 0.4246948 0.18036571
## 9: 0.9051625 c -0.7536128 0.56793224# Multiple operations
DT[,m:={tmp <-(x+z); log2(tmp+5)}]
DT## x y z w m
## 1: -0.1386099 a -0.7537332 0.56811370 2.038316
## 2: 1.4045568 a -0.5424090 0.29420755 2.551429
## 3: -1.2711654 a 1.3848216 1.91773090 2.354355
## 4: 0.9479388 b 0.2464019 0.06071388 2.630951
## 5: 0.4464590 b 1.9812184 3.92522635 2.892911
## 6: -0.5842602 b -0.1435037 0.02059332 2.094991
## 7: 0.3548485 c -0.1427674 0.02038253 2.381860
## 8: -0.2297939 c 0.4246948 0.18036571 2.377096
## 9: 0.9051625 c -0.7536128 0.56793224 2.365007# Special variables
set.seed(123)
DT <-data.table(x = sample(letters[1:3],1E5,TRUE))
DT[,.N,by = x]## x N
## 1: c 33294
## 2: b 33305
## 3: a 33401# Use of keys
DT <- data.table(x = rep(c("a","b","C"),each = 100), y = rnorm(300))
setkey(DT,x)
DT['a']## x y
## 1: a 0.88631257
## 2: a 2.82858132
## 3: a 2.03145429
## 4: a 1.90675413
## 5: a 0.21490826
## 6: a -0.86273413
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## x yThe use of keys facilitates the joins of data sets.
DT1 <- data.table(x = c("a","b","b","dt1"), y = 1:4)
DT2 <- data.table(x = c("a", "b", "dt2"), z = 5:7)
setkey(DT1,x)
setkey(DT2,x)
merge(DT1,DT2)## x y z
## 1: a 1 5
## 2: b 2 6
## 3: b 3 6Fast reading
# big_df <- data.frame(x = rnorm(1E6), y = rnorm(1E6))
# file <- tempfile()
# write.table(big_df, file = file, row.names = FALSE, col.names = TRUE, sep = "\t", quote = FALSE)
# system.file(fread(file))
# system.time(read.table(file, header = TRUE, sep = "\t"))Connecting and listing databases. Do not forget to disconnect from the server.
# install.packages("RMySQL")
library(RMySQL)## Warning: package 'RMySQL' was built under R version 3.6.3## Loading required package: DBIucscDb <- dbConnect(MySQL(), user = "genome", host = "genome-mysql.cse.ucsc.edu")
result <-dbGetQuery(ucscDb,"show databases;")
dbDisconnect(ucscDb)## [1] TRUEhg19 <- dbConnect(MySQL(), user = "genome", db = "hg19", host = "genome-mysql.cse.ucsc.edu")
allTables <- dbListTables(hg19)
length(allTables)## [1] 12587allTables[1:6]## [1] "HInv" "HInvGeneMrna" "acembly" "acemblyClass" "acemblyPep"
## [6] "affyCytoScan"dbListFields(hg19, "affyU133Plus2")## [1] "bin" "matches" "misMatches" "repMatches" "nCount"
## [6] "qNumInsert" "qBaseInsert" "tNumInsert" "tBaseInsert" "strand"
## [11] "qName" "qSize" "qStart" "qEnd" "tName"
## [16] "tSize" "tStart" "tEnd" "blockCount" "blockSizes"
## [21] "qStarts" "tStarts"dbGetQuery(hg19, "select count(*) from affyU133Plus2")## count(*)
## 1 58463# Read from the table
affyData <- dbReadTable(hg19, "affyU133Plus2")## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 0 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 1 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 2 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 3 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 4 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 5 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 6 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 7 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 8 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 11 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 12 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 13 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 15 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 16 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 17 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 18 imported as
## numerichead(affyData)## bin matches misMatches repMatches nCount qNumInsert qBaseInsert tNumInsert
## 1 585 530 4 0 23 3 41 3
## 2 585 3355 17 0 109 9 67 9
## 3 585 4156 14 0 83 16 18 2
## 4 585 4667 9 0 68 21 42 3
## 5 585 5180 14 0 167 10 38 1
## 6 585 468 5 0 14 0 0 0
## tBaseInsert strand qName qSize qStart qEnd tName tSize tStart
## 1 898 - 225995_x_at 637 5 603 chr1 249250621 14361
## 2 11621 - 225035_x_at 3635 0 3548 chr1 249250621 14381
## 3 93 - 226340_x_at 4318 3 4274 chr1 249250621 14399
## 4 5743 - 1557034_s_at 4834 48 4834 chr1 249250621 14406
## 5 29 - 231811_at 5399 0 5399 chr1 249250621 19688
## 6 0 - 236841_at 487 0 487 chr1 249250621 27542
## tEnd blockCount
## 1 15816 5
## 2 29483 17
## 3 18745 18
## 4 24893 23
## 5 25078 11
## 6 28029 1
## blockSizes
## 1 93,144,229,70,21,
## 2 73,375,71,165,303,360,198,661,201,1,260,250,74,73,98,155,163,
## 3 690,10,32,33,376,4,5,15,5,11,7,41,277,859,141,51,443,1253,
## 4 99,352,286,24,49,14,6,5,8,149,14,44,98,12,10,355,837,59,8,1500,133,624,58,
## 5 131,26,1300,6,4,11,4,7,358,3359,155,
## 6 487,
## qStarts
## 1 34,132,278,541,611,
## 2 87,165,540,647,818,1123,1484,1682,2343,2545,2546,2808,3058,3133,3206,3317,3472,
## 3 44,735,746,779,813,1190,1195,1201,1217,1223,1235,1243,1285,1564,2423,2565,2617,3062,
## 4 0,99,452,739,764,814,829,836,842,851,1001,1016,1061,1160,1173,1184,1540,2381,2441,2450,3951,4103,4728,
## 5 0,132,159,1460,1467,1472,1484,1489,1497,1856,5244,
## 6 0,
## tStarts
## 1 14361,14454,14599,14968,15795,
## 2 14381,14454,14969,15075,15240,15543,15903,16104,16853,17054,17232,17492,17914,17988,18267,24736,29320,
## 3 14399,15089,15099,15131,15164,15540,15544,15549,15564,15569,15580,15587,15628,15906,16857,16998,17049,17492,
## 4 14406,20227,20579,20865,20889,20938,20952,20958,20963,20971,21120,21134,21178,21276,21288,21298,21653,22492,22551,22559,24059,24211,24835,
## 5 19688,19819,19845,21145,21151,21155,21166,21170,21177,21535,24923,
## 6 27542,# Select a specific subset
query <- dbSendQuery(hg19, "select * from affyU133Plus2 where MisMatches between 1 and 3")## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 0 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 1 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 2 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 3 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 4 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 5 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 6 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 7 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 8 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 11 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 12 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 13 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 15 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 16 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 17 imported as
## numeric## Warning in .local(conn, statement, ...): Unsigned INTEGER in col 18 imported as
## numericaffyMis <- fetch(query)
quantile(affyMis$misMatches)## 0% 25% 50% 75% 100%
## 1 1 2 2 3affyMisSmall <- fetch(query, n= 10)
dbClearResult(query)## [1] TRUEdim(affyMisSmall)## [1] 10 22# if (!require("BiocManager", quietly = TRUE))
# install.packages("BiocManager")
# BiocManager::install()
# biocLite("rhdf5")Open a connection and do not forget to close the connection.
con <- url("https://scholar.google.com.mx/citations?user=8ODrYesAAAAJ&hl=es")
htmlCode <- readLines(con)## Warning in readLines(con): incomplete final line found on 'https://
## scholar.google.com.mx/citations?user=8ODrYesAAAAJ&hl=es'close(con)
htmlCode## [1] "<!doctype html><html><head><title>Jorge Arturo Garza Venegas - Google Académico</title><meta http-equiv=\"Content-Type\" content=\"text/html;charset=ISO-8859-1\"><meta http-equiv=\"X-UA-Compatible\" content=\"IE=Edge\"><meta name=\"referrer\" content=\"always\"><meta name=\"viewport\" content=\"width=device-width,initial-scale=1,minimum-scale=1,maximum-scale=2\"><meta name=\"format-detection\" content=\"telephone=no\"><link rel=\"shortcut icon\" href=\"/favicon.ico\"><link rel=\"canonical\" href=\"https://scholar.google.com.mx/citations?user=8ODrYesAAAAJ&hl=es\"><meta name=\"description\" content=\"Tecnologico de Monterrey - Citado por 18 - Statistical Process Monitoring - Time series - parametric methods\"><meta property=\"og:description\" content=\"Tecnologico de Monterrey - Citado por 18 - Statistical Process Monitoring - Time series - parametric methods\"><meta property=\"og:title\" content=\"Jorge Arturo Garza Venegas\"><meta property=\"og:image\" 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## [41] "xb.add(function(){var a=sb(window.location.hash),b=a.d||\"\",c=b?A(b):null;++Zc;if(c){var d=a.u||\"\";c=0<+a.p;var e=+a.t||0,f=L||K(window.history.state)||{};a=+f.n||0;var h=\"\"+(f.p||\"\");f=\"\"+(f.h||\"\");d.match(Ja)||(d=\"\");for(var l=Mc(T,e),n=l;n<T.l.length;++n){var m=T.at(n);if(e<m.C&&m.i!=b)break}for(m=l-1;0<=m;--m){var t=T.at(m);if(e>t.C&&t.i!=b)break}Lc(n-1);for(n=0;n<=m;++n)t=T.at(n).i,I[t]||Oc(m,!1);if(m=l<T.l.length)m=T.at(l),m=b==m.i&&d==m.F&&c==!!m.D&&e==m.C;m?Oc(l,!0):(0==a&&(Lc(-1),T=new Kc,"
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## [43] "ed.prototype.pa=function(a){var b=this;N(a);if((a=this.K)&&!this.m){var c=\"json=&\"+Da(a);fd(this,!0);this.m=Wb(a.action,c,function(d,e){b.m=null;fd(b,!1);var f=b.K,h=f.getAttribute(\"data-alrt\");if(h=h?A(h):null)h.innerHTML=\"\";try{var l=200==d&&JSON.parse(e)}catch(E){}d=!1;l&&\"object\"==typeof l||(gd(h,A(\"gs_md_err\").innerHTML),l={},d=!0);f.setAttribute(\"data-p\",\"\"+(l.P||\"\"));P(\"gs-ajax-form-done\",f);if(e=l.L)Ha(\"\"+e);else{if(e=l.M)gd(h,e),d=!0;e=1E6;if(h&&h.innerHTML){var n=h;e=h.getBoundingClientRect().top}h="
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## [45] "var fd=function(a,b){a=a.K;var c=a.getAttribute(\"data-bsel\");a=c?document.querySelectorAll(c):a.querySelectorAll(\"button\");for(c=a.length;c--;){var d=a[c];d.disabled=b;v(d,\"gs_bsp\",b)}},gd=function(a,b){if(a)a.innerHTML=b;else{var c=void 0===c?\"\":c;var d=void 0===d?\"\":d;var e=void 0===e?[]:e;A(\"gs_alrt_m\").innerHTML=b;Rb().action=d.match(Ga)?d:\"\";a=A(\"gs_alrt_l\");a.textContent=c;c=A(\"gs_alrt_h\");c.innerHTML=\"\";for(var f in e)b=document.createElement(\"input\"),b.type=\"hidden\",b.name=f,b.value=e[f],"
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## [49] "!1,!0);Q(\".gs_fm_s\",\"click\",function(a){a=a.currentTarget.getAttribute(\"data-fm\")||\"\";(a=A(a))&&a.submit()});var V=function(a){this.i=Aa(a.querySelector(\".gs_md_d\"));this.R=Aa(a.querySelector(\".gs_md_tb\"))};V.prototype.T=function(a){var b=A(this.i);return void 0!==a?xc(b,b,a):null};V.prototype.open=function(a){a=this.T(a);if(u(A(this.R),\"gs_sel\"))try{a&&a.focus()}catch(c){}else{var b=A(this.R);ab(this.i,function(){q(b,\"gs_sel\")},function(){r(b,\"gs_sel\")},a,b)}};V.prototype.close=function(){fb(this.i)};V.prototype.ha=function(a){N(a);u(A(this.R),\"gs_sel\")?this.close():this.open(\"keydown\"==a.g.type?!1:void 0)};"
## [50] "V.prototype.ca=function(a){var b=a.g.keyCode;if(38==b||40==b)N(a),this.open(38==b)};V.prototype.ja=function(a){a.target.id==this.i&&this.ca(a)};$b(V,[new O(\".gs_md_rmb\",{}),new O(\".gs_md_tb\",{\"gs-press\":V.prototype.ha,keydown:V.prototype.ca}),new O(\".gs_md_d\",{keydown:V.prototype.ja})]);var od=function(a){V.call(this,a);this.ra=Aa(a.querySelector(\".gs_md_in\"));this.sa=Aa(a.querySelector(\".gs_md_tb .gs_lbl\"))};ka(od,V);od.prototype.T=function(){return A(this.i).querySelector(\".gs_md_li[aria-selected]\")};od.prototype.ka=function(a){pd(this,a)};od.prototype.U=function(a){var b=a.g.keyCode;13!=b&&32!=b||pd(this,a)};"
## [51] "var pd=function(a,b){var c=b.currentTarget,d=A(a.ra),e=a.T();c!=e&&(d.value=c.getAttribute(\"data-v\"),A(a.sa).innerHTML=c.innerHTML,e&&qd(e,!1),qd(c,!0));N(b);a.close();P(\"gs-change\",d,b.g)},qd=function(a,b){v(a,\"gs_sel\",b);b?a.setAttribute(\"aria-selected\",\"true\"):a.removeAttribute(\"aria-selected\")};$b(od,[new O(\".gs_md_ris\",{}),new O(\".gs_md_li\",{click:od.prototype.ka,keydown:od.prototype.U})]);Q(\"#gs_lp\",\"click\",function(a){N(a);U(\"gs_lp_d\")});Q(\"#gs_lp_cur\",\"click\",function(a){N(a);fb(\"gs_lp_d\")});var rd=function(a){this.ea=Aa(a)};rd.prototype.U=function(a){var b=a.currentTarget,c=a.g.keyCode;if(38==c||40==c){var d=A(this.ea);d=xc(d,b,38==c)||xc(d,d,38==c)}else if(37==c||39==c)a:{c=!!(37==c^Ca(b.parentNode));d=b.parentNode;var e=d.children,f=e.length;if(d.id!=this.ea){for(;e[--f]!=b;);d=wc(d,c)||vc(d.parentNode,c);e=d.children;if(f=Math.min(f+1,e.length))if(d=e[f-1],u(d,\"gs_md_li\")&&d.offsetLeft!=b.offsetLeft)break a}d=void 0}d&&(N(a),d.focus())};"
## [52] "$b(rd,[new O(\".gs_md_ulr\",{}),new O(\".gs_md_li\",{keydown:rd.prototype.U})]);Q(\"#gs_hdr_mnu\",\"click\",function(a){N(a);U(\"gs_hdr_drw\")});Q(\"#gs_hdr_drw_mnu\",\"click\",function(a){N(a);fb(\"gs_hdr_drw\")});Q(\"#gs_hdr_act_i\",\"click\",function(a){N(a);1==sa()?Ha(document.querySelector(\"#gs_hdr_drw_bot>a\").href):ab(\"gs_hdr_act_d\")});Q(\"#gs_hdr_drw\",\"keydown\",function(a){var b=a.g.keyCode;if(38==b||40==b){var c=a.currentTarget;if(b=xc(c,c,38==b))N(a),b.focus()}});"
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## [54] "Q(\"#gs_hdr_tsc\",\"mousedown\",function(a){N(a);var b=A(\"gs_hdr_tsi\");b.value=\"\";b.focus();P(\"input\",b,a.g)});Q(\"#gs_hdr_sre\",\"click\",function(a){N(a);var b=A(\"gs_hdr\");ab(\"gs_hdr_frm\",function(){r(b,\"gs_hdr_src\");q(b,\"gs_hdr_srx\")},function(){q(b,\"gs_hdr_src\");r(b,\"gs_hdr_srx\")},A(\"gs_hdr_tsi\"))});Q(\".gs_md_x\",\"click\",function(a){(a=a.currentTarget.getAttribute(\"data-mdx\"))&&fb(a)});var W=function(){},sd,td;W.prototype.ia=function(a){a.g.button||(N(a),ud(a))};W.prototype.la=function(a){vd(a)&&(N(a),ud(a))};W.prototype.ma=function(a){vd(a)&&N(a)};W.prototype.na=function(a){if(!a.g.button){N(a);var b=a.g;b&&(wd=b.clientX||0,xd=b.clientY||0,C(document,yd,zd,!0),clearTimeout(sd),sd=setTimeout(Ad,2E3));ud(a)}};W.prototype.qa=function(a){N(a);if(Bd){var b=a.g;if(b=(b=b&&b.touches)&&1==b.length&&b[0])Cd=b.clientX,Dd=b.clientY,C(document,Ed,Fd,!0),clearTimeout(td),td=setTimeout(Gd,2E3)}ud(a)};"
## [55] "var vd=function(a){a=a.g.keyCode;return 32==a||13==a},ud=function(a){P(\"gs-press\",a.currentTarget,a.g)},Ad=function(){G(document,yd,zd,!0);clearTimeout(sd);sd=void 0},zd=function(a){\"mousedown\"!=a.type&&10>Math.abs(a.clientX-wd)&&10>Math.abs(a.clientY-xd)?(Ta(a),\"click\"==a.type&&Ad()):Ad()},Gd=function(){G(document,Ed,Fd,!0);clearTimeout(td);td=void 0},Fd=function(a){\"touchstart\"!=a.type&&10>Math.abs(a.clientX-Cd)&&10>Math.abs(a.clientY-Dd)?(Ta(a),\"click\"==a.type&&Gd()):Gd()},wd=0,xd=0,yd=[\"mousedown\","
## [56] "\"mouseup\",\"click\"],Bd=x(\"Android\")&&!x(\"Chrome\"),Cd=0,Dd=0,Ed=[\"touchstart\",\"mousedown\",\"mouseup\",\"click\"];$b(W,[new O(\".gs_press\",{click:W.prototype.ia,keydown:W.prototype.la,keyup:W.prototype.ma,mousedown:W.prototype.na,touchstart:W.prototype.qa})]);function Hd(a){Id.style.left=Jd&&Kd===Ld?a.left+\"px\":\"auto\";Id.style.width=Jd?a.width+\"px\":\"auto\";P(\"gs-sth-change\",A(\"gs_sth\"))}function Md(){var a=Nd.getBoundingClientRect(),b=a.top,c=Id.offsetHeight,d=0>b,e;if(e=d&&pa)e=document.activeElement,e=!!e&&\"INPUT\"==e.tagName&&\"text\"==e.type;b=e?-b-a.height:Ld;var f=Jd!=d||Kd!==Ld!=e;b!==Kd&&(Kd=b,Id.style.transform=b===Ld?\"none\":\"translate3d(0,\"+b+\"px,0)\");f&&(Jd=d,v(Od,\"gs_sth_vis\",d),v(Od,\"gs_sth_trk\",e),Hd(a),Nd.style.height=Jd?c+\"px\":\"auto\")}"
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## [64] "Q([\"#gsc_coauth_opn\",\".gsc_rsb_btne\",\".gsc_rsb_btnv\"],\"click\",function(){Zd(\"gsc_cod_lc\");ee=0;X.clear();Y.clear();var a=be();a&&(a.value=\"\");ae()});Q(\".gsc_rsb_aa\",[\"click\",\"keydown\"],function(a){if(\"keydown\"!=a.type||a.g&&!Ua(a.g)&&13==a.g.keyCode)a.g&&Ta(a.g),(a=(a=a.currentTarget.querySelector(\"a\"))?a.getAttribute(\"href\"):\"\")&&Ha(a)});Q(\"#gsc_prf_t-ath\",\"click\",function(){Qd()});H(function(){Gc.add(te);te()});Q(\".gsc_lwpds_frm\",\"submit\",function(a){N(a);P(\"gsc-lwpds-submit\",a.target)});"
## [65] "var ze=window.location.href.split(\"#\")[0];me=ze.replace(/([?&])(cstart|pagesize)=[^&]*/g,\"$1\");ne=Math.max(+ze.replace(/.*[?&]cstart=([^&]*).*/,\"$1\")||0,0);oe=+ze.replace(/.*[?&]pagesize=([^&]*).*/,\"$1\")||0;oe=Math.max(Math.min(oe,100),20);"
## [66] "Q(\"#gsc_bpf_more\",\"click\",function(a){var b=a.currentTarget,c=oe,d=100>c?100-c:100;a=(me+\"&cstart=\"+(ne+c)+\"&pagesize=\"+d).replace(/([?&])&+/g,\"$1\");he(0);b.disabled=!0;Wb(a,\"json=1\",function(e,f){b.disabled=!1;try{var h=200==e&&JSON.parse(f)}catch(n){}if(h&&\"object\"==typeof h){oe=c+=d;he(1);f=\"\"+h.B;e=A(\"gsc_a_b\");var l=document.createElement(za.ga);l.innerHTML=f;f=Array.prototype.slice.call(l.rows);for(l=0;l<f.length;l++)e.appendChild(f[l]);ke();if(e=A(\"gsc_a_nn\"))f=e.innerHTML.replace(/[0-9]+$/,"
## [67] "\"\"+A(\"gsc_a_b\").rows.length),e.innerHTML=f;b.disabled=!h.N}else he(2)})});Q([\"#gsc_fol_a\",\"#gsc_fol_c\",\"#gsc_fol_r\"],\"gs-change\",re);Q(\"#gsc_fol_m\",\"input\",re);Q(\"#gsc_fol_f\",\"submit\",function(a){a.g&&a.g.preventDefault();a=A(\"gsc_fol_f\");var b=A(\"gsc_fol_inp\");b.innerHTML=\"\";for(var c=pe(zc),d=pe(Ac),e=0;e<c.length;e++)if(c[e]!=d[e]){var f=se[e],h=document.createElement(\"input\");h.type=\"hidden\";h.name=c[e]?f:\"un\"+f;b.appendChild(h)}P(\"gsc-fol-submit\",a)});Q(\"#gsc_fol_f\",\"gsc-fol-submit\",function(a){a.currentTarget.submit()});"
## [68] "Q(\"#gsc_md_hist\",\"gs-md-lded\",function(){var a=A(\"gsc_md_hist_c\");if(!a.innerHTML){var b=document.getElementsByClassName(\"gsc_g_hist_wrp\");1==b.length&&(a.appendChild(b[0].cloneNode(!0)),ue(a.lastChild))}});Q([\"#gsc_hist_opn\",\".gsc_md_hist_b\"],\"click\",function(){var a=document.documentElement;!A(\"gsc_hist_opn\")||u(a,\"gs_el_ph\")||u(a,\"gs_el_ta\")||U(\"gsc_md_hist\")});"
## [69] "Q(\"#gsc_lwp_mndt_lnk\",\"click\",function(a){var b=a.currentTarget.getAttribute(\"href\")||\"\";b+=\"&tzom=\"+(new Date).getTimezoneOffset();Ha(b);a.g.preventDefault()});Q(\"#gsc_prf_btne\",\"click\",function(){var a=A(\"gsc_md_pro_f\");a.reset();a=a.querySelectorAll(\".gs_in_txtw\");for(var b=a.length;b--;){var c=a[b];r(c,\"gs_in_txte\");c.querySelector(\".gs_in_txts\").innerHTML=\"\"}a=A(\"gsc_md_pro-d\");a.setAttribute(\"data-ifc\",\"\");U(a.id,pb({t:\"gsc_md_pro_ed\"}))});Q(\"#gsc_prf_btnf\",\"click\",function(){U(\"gsc_md_fol\")});"
## [70] "Q(\"#gsc_md_fol_pub\",\"click\",function(){A(\"gsc_fol_mpf\").submit()});Q(\"#gsc_prf_iv_tg\",\"click\",function(){v(A(\"gsc_prf_w\"),\"gsc_prf_why\")});Q(\".gsc_prf_pel\",[\"click\",\"keydown\"],function(a){(\"keydown\"!=a.type||13==a.g.keyCode&&a.g&&!Ua(a.g))&&ve()});Q(\"#gsc_prf_pufii\",\"change\",function(){A(\"gsc_prf_puf\").submit()});Q(\"#gsc_prf_ion_btn\",\"click\",function(){v(A(\"gsc_prf_ion\"),\"gs_prf_ion_show\")});"
## [71] "Q(\".gsc_prf_tab\",\"click\",function(a){var b=A(\"gsc_bdy\");b.setAttribute(\"data-tab\",a.currentTarget.id);b=b.querySelectorAll(\".gsc_prf_tab\");for(var c=0;c<b.length;c++){var d=b[c];d.setAttribute(\"aria-selected\",\"\"+(d==a.currentTarget))}});H(function(){Gc.add(we);we()});Q(\"#gsc_md_cbyd\",\"gs-md-ldin\",function(){var a=A(\"gsc_md_cbyd_merge\");a&&(a.disabled=!0);Fa(\"\")});"
## [72] "Q(\"#gsc_md_cbyd\",\"gs-md-lded\",function(){var a=A(\"gsc_md_cbyd_f\"),b=A(\"gsc_md_cbyd_merge\"),c=cd(\"gsc_md_cbyd\"),d=tb(c).s||\"\";c=sb(c).c||\"\";a.elements.s.value=d;Fa(c);b&&a.elements.choose&&(b.disabled=!1,b.getBoundingClientRect().bottom<window.innerHeight&&b.focus())});"
## [73] "Q(\"#gsc_md_cbym\",[\"gs-md-ldin\",\"gs-md-lded\"],function(){var a=cd(\"gsc_md_cbym\");a=tb(a).s||\"\";var b=A(\"gsc_md_cbym_e\");b&&a&&0>a.indexOf(\"&\")&&b.setAttribute(\"data-href\",(b.getAttribute(\"data-href\")||\"\").replace(/(&citation_for_view=)[^&]*/,\"$1\"+a))});Q(\"#gsc_md_cbym_e\",\"click\",function(a){a=a.currentTarget.getAttribute(\"data-href\")||\"\";U(\"gs_md_cita-d\",a)});$b(Vd,Wd);H(function(){return setTimeout(ke,0)});Q(\".gsc_a_x\",\"change\",ke);"
## [74] "Q(\"#gsc_x_all\",\"gs-change\",function(a){a=zc(a.currentTarget);for(var b=2==a?le:ie(),c=b.length;c--;)b[c].checked=0!=a;je()});Q(\".gsc_a_acm\",\"click\",function(a){N(a);var b=a.currentTarget;a=b.href;var c=b.getAttribute(\"data-eid\")||\"\";b=(b.getAttribute(\"data-eud\")||\"\")+\",\"+c;a=A(\"gsc_md_cbyd_f\").action+\"&update_op=merge_options&s=\"+b+pb({c:a});U(\"gsc_md_cbyd\",a)});"
## [75] "Q(\".gsc_a_am\",\"click\",function(a){a=a.currentTarget.getAttribute(\"data-eid\")||\"\";a=(A(\"gsc_md_cbym_l\").getAttribute(\"data-act\")||\"\")+\"&update_op=merge_options&s=\"+a;U(\"gsc_md_cbym\",a)});Q(\"#gs_sth\",\"gs-sth-change\",function(a){var b=A(\"gsc_a_tr0\"),c=A(\"gsc_a_trh\");b=b.querySelector(\".gsc_a_t\");c.querySelector(\".gsc_a_t\").style.width=u(a.currentTarget,\"gs_sth_vis\")?b.offsetWidth+\"px\":\"auto\"});"
## [76] "Q(\"#gs_md_cita-b-save\",\"click\",function(){var a=A(\"gsc_ecd_form\");Ea(a,\"continue\").value=window.location.pathname+window.location.search;P(\"submit\",a)});Q(\".gsc_ecd_form_tsel\",\"click\",function(a){var b=A(\"gsc_ecd_form\"),c=A(\"gsc_ecd_table\");b=Ea(b,\"articletype\");a=a.currentTarget;b.value=a.getAttribute(\"data-type\")||\"\";c.className=a.getAttribute(\"data-class\")||\"\";c=document.querySelectorAll(\"#gsc_ecd_citation_type button\");for(b=c.length;b--;)v(c[b],\"gs_sel\",c[b]==a)});"
## [77] "}({\"customAC\":0,\"eventId\":\"c9mcY5-iHoTTsQKamIhY\"});</script></head><body><div id=\"gs_top\" onclick=\"\"><style>#gs_md_s,.gs_md_wnw{z-index:1200;position:fixed;top:0;left:0;width:100%;height:100%;visibility:hidden;}.gs_md_ds:before{content:'';position:absolute;background-color:#fff;z-index:100;opacity:0;visibility:hidden;top:0;bottom:0;right:0;left:0;}.gs_md_ds.gs_md_d:not(.gs_el_ph .gs_md_wmw):before{top:-1px;bottom:-1px;right:-1px;left:-1px;}#gs_md_s{background-color:#fff;opacity:0;}.gs_el_ta #gs_md_s,.gs_el_ph #gs_md_s,.gs_el_ta .gs_md_ds:before,.gs_el_ph .gs_md_ds:before{background-color:#666;}#gs_md_s.gs_vis,.gs_md_ds.gs_md_ins_vis:before{opacity:.5;visibility:visible;}.gs_md_wnw{transition:all 0s .218s;}.gs_md_wnw.gs_vis{visibility:visible;transition:all 0s;}.gs_el_tc .gs_md_ds:before{transition:opacity .15s,visibility 0s .15s;}.gs_el_tc .gs_md_ds.gs_md_ins_vis:before{transition:opacity .218s,visibility 0s;}.gs_md_wnw>.gs_md_d{position:relative;margin:0 auto;width:464px;box-shadow:2px 2px 8px rgba(0,0,0,.2);white-space:normal;}.gs_el_ta .gs_md_wnw>.gs_md_d,.gs_el_ph .gs_md_wnw>.gs_md_d{box-shadow:2px 2px 8px rgba(0,0,0,.65);}.gs_el_ph .gs_md_wnw>.gs_md_d{width:80%;max-width:440px;}.gs_el_ph .gs_md_wmw>.gs_md_d{display:flex;flex-direction:column;width:100%;height:100%;max-width:none;border:none;box-shadow:none;transform:translate(0,100%);transform:translate(0,100vh);transition:transform .27s cubic-bezier(.4,0,.6,1),opacity 0s .27s,visibility 0s .27s,max-height 0s .27s;}.gs_el_ph .gs_md_wmw>.gs_md_d.gs_vis{transform:translate(0,0);transition:transform .3s cubic-bezier(0,0,.2,1);}.gs_md_wmw>.gs_md_d.gs_abt,.gs_el_ph .gs_md_wmw>.gs_md_d.gs_abt{transition:none;}.gs_md_hdr{display:flex;align-items:center;height:47px;border-bottom:1px solid #e0e0e0;border-bottom-color:rgba(0,0,0,.12);background-color:#f5f5f5;}.gs_md_hdr>a,.gs_md_hdr>a.gs_btn_lrge{flex:0 0 auto;width:41px;height:47px;}.gs_el_ph .gs_md_hdr>a{margin:0 2px 0 0;}.gs_el_ph a.gs_md_hdr_c{margin:0 0 0 2px;}.gs_md_hdr_b{margin:0 41px 0 16px;}.gs_el_ph .gs_md_hdr_b{margin:0 16px;}.gs_md_hdr_t:empty~.gs_md_hdr_b{margin-left:0;}.gs_md_hdr_b:empty{width:41px;margin:0;}.gs_el_ph .gs_md_hdr_b:empty{margin-right:2px;}.gs_md_hdr_b:empty:not(:last-child){display:none;}.gs_md_hdr_b>button{min-width:51px;height:33px;}.gs_md_hdr_t{flex:1 1 auto;font-size:18px;font-weight:normal;color:#666;overflow:hidden;text-overflow:ellipsis;white-space:nowrap;text-align:center;}.gs_md_bdy{position:relative;overflow-y:auto;box-sizing:border-box;padding:24px 41px 0 41px;}.gs_md_bdy:after{display:block;content:\"\";clear:both;padding-bottom:24px;}.gs_el_ph .gs_md_bdy{padding:16px 16px 0 16px;}.gs_el_ph .gs_md_bdy:after{padding-bottom:16px;}.gs_el_ph .gs_md_wmw .gs_md_bdy{flex:1;}.gs_md_ftr{border-top:1px solid #e0e0e0;}.gs_md_lbl{display:block;font-size:16px;margin:0 0 16px 0;word-wrap:break-word;}.gs_md_btns{margin:24px 0 0 0;white-space:nowrap;}.gs_el_ph .gs_md_btns{margin:16px 0 0 0;}.gs_md_btns button{margin-right:16px;}.gs_md_btns button:last-child{margin-right:0;}.gs_md_prg{margin:24px 0;text-align:center;}.gs_md_prg .gs_alrt{padding:4px 16px;}.gs_md_ldg:before{content:\"\";position:absolute;top:0;left:0;bottom:0;right:0;background-color:#fff;opacity:.5;z-index:100;}</style><div id=\"gs_md_ldg\" style=\"display:none\">Cargando...</div><div id=\"gs_md_err\" style=\"display:none\">El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.</div><div id=\"gs_md_s\"></div><div data-h=\"0\" class=\"gs_md_wnw gs_md_ds\"><div id=\"gsc_md_hist\" class=\"gs_md_d gs_md_ds gs_ttzi\" role=\"dialog\" tabindex=\"-1\" aria-labelledby=\"gsc_md_hist-t\" data-wfc=\"gsc_md_hist-x\"><div class=\"gs_md_hdr\"><a href=\"javascript:void(0)\" id=\"gsc_md_hist-x\" role=\"button\" aria-label=\"Cancelar\" data-mdx=\"gsc_md_hist\" class=\"gs_btnCLS gs_md_x gs_md_hdr_c gs_in_ib gs_btn_lrge\"><span class=\"gs_ico\"></span><span class=\"gs_ia_notf\"></span><span class=\"gs_lbl\"></span></a><h2 id=\"gsc_md_hist-t\" class=\"gs_md_hdr_t\">Citas por año</h2><div class=\"gs_md_hdr_b\"></div></div><div id=\"gsc_md_hist-bdy\" class=\"gs_md_bdy\"><style>#gsc_md_hist{width:80%;max-width:386px;}#gsc_md_hist_c{position:relative;width:100%;}</style><div id=\"gsc_md_hist_c\"></div></div></div></div><div data-h=\"600\" class=\"gs_md_wnw gs_md_ds gs_md_wmw\"><div id=\"gsc_md_cbyd\" class=\"gs_md_d gs_md_ds gs_ttzi\" role=\"dialog\" tabindex=\"-1\" aria-labelledby=\"gsc_md_cbyd-t\" data-cid=\"gsc_md_cbyd_l\" data-wfc=\"gsc_md_cbyd-x\"><div class=\"gs_md_hdr\"><a href=\"javascript:void(0)\" id=\"gsc_md_cbyd-x\" role=\"button\" aria-label=\"Cancelar\" data-mdx=\"gsc_md_cbyd\" class=\"gs_btnCLS gs_md_x gs_md_hdr_c gs_in_ib gs_btn_lrge\"><span class=\"gs_ico\"></span><span class=\"gs_ia_notf\"></span><span class=\"gs_lbl\"></span></a><h2 id=\"gsc_md_cbyd-t\" class=\"gs_md_hdr_t\">Citas duplicadas</h2><div class=\"gs_md_hdr_b\"></div></div><div id=\"gsc_md_cbyd-bdy\" class=\"gs_md_bdy\"><form id=\"gsc_md_cbyd_f\" action=\"/citations?hl=es&oe=ASCII&user=8ODrYesAAAAJ&view_op=list_works\" method=\"post\"><input type=\"hidden\" name=\"s\" value=\"\"><div class=\"gs_md_lbl\">Los artículos siguientes se han combinado en Google Académico. Sus correspondientes <a id=\"gsc_md_cbyd_c\" href=\"javascript:void(0)\">citas combinadas</a> se computan solo para el primer artículo.</div><div id=\"gsc_md_cbyd_l\"></div></form></div></div></div><div data-h=\"600\" class=\"gs_md_wnw gs_md_ds gs_md_wmw\"><div id=\"gsc_md_cbym\" class=\"gs_md_d gs_md_ds gs_ttzi\" role=\"dialog\" tabindex=\"-1\" aria-labelledby=\"gsc_md_cbym-t\" data-cid=\"gsc_md_cbym_l\" data-wfc=\"gsc_md_cbym-x\"><div class=\"gs_md_hdr\"><a href=\"javascript:void(0)\" id=\"gsc_md_cbym-x\" role=\"button\" aria-label=\"Cancelar\" data-mdx=\"gsc_md_cbym\" class=\"gs_btnCLS gs_md_x gs_md_hdr_c gs_in_ib gs_btn_lrge\"><span class=\"gs_ico\"></span><span class=\"gs_ia_notf\"></span><span class=\"gs_lbl\"></span></a><h2 id=\"gsc_md_cbym-t\" class=\"gs_md_hdr_t\">Citas combinadas</h2><div class=\"gs_md_hdr_b\"></div></div><div id=\"gsc_md_cbym-bdy\" class=\"gs_md_bdy\"><div class=\"gs_md_lbl\">La lista denominada Citados por incluye las citas a los siguientes artículos de Google Académico. Los que se indican como <span id=\"gsc_md_cbym_s\">*</span> pueden diferir del artículo que aparece en el perfil.</div><div id=\"gsc_md_cbym_l\" data-act=\"/citations?hl=es&oe=ASCII&user=8ODrYesAAAAJ&view_op=list_works\"></div></div></div></div><div data-h=\"900\" class=\"gs_md_wnw gs_md_ds gs_md_wmw\"><div id=\"gsc_md_cod\" class=\"gs_md_d gs_md_ds gs_ttzi gsc_cod_lc\" role=\"dialog\" tabindex=\"-1\" aria-labelledby=\"gsc_md_cod-t\" data-cid=\"gsc_cods_res\" data-wfc=\"gsc_md_cod-x\"><div class=\"gs_md_hdr\"><a href=\"javascript:void(0)\" id=\"gsc_md_cod-x\" role=\"button\" aria-label=\"Cancelar\" data-mdx=\"gsc_md_cod\" class=\"gs_btnCLS gs_md_x gs_md_hdr_c gs_in_ib gs_btn_lrge\"><span class=\"gs_ico\"></span><span class=\"gs_ia_notf\"></span><span class=\"gs_lbl\"></span></a><h2 id=\"gsc_md_cod-t\" class=\"gs_md_hdr_t\"><span id=\"gsc_cod_t\"><span id=\"gsc_cod_tadd\">Añadir coautores</span><span id=\"gsc_cod_tedit\">Coautores</span><a id=\"gsc_cod_trev\" href=\"javascript:void(0)\" data-txt=\"Revisar\" data-lim=\"Se ha alcanzado el límite\"></a></span></h2><div class=\"gs_md_hdr_b\"><button type=\"button\" id=\"gsc_cod_done\" aria-label=\"Añadir coautores\" disabled class=\"gs_btnDNW gs_in_ib gs_btn_act gs_btn_half gs_btn_lsb\"><span class=\"gs_wr\"><span class=\"gs_ico\"></span><span class=\"gs_lbl\"></span></span></button></div></div><div id=\"gsc_md_cod-bdy\" class=\"gs_md_bdy\"><div id=\"gsc_cods_urls\" class=\"gsc_cods_hide\" data-ls=\"\" data-lc=\"/citations?view_op=list_colleagues&hl=es&oe=ASCII&json=&user=8ODrYesAAAAJ\" data-sa=\"\"></div><form id=\"gsc_cods_save\" action=\"\" method=\"POST\"><input type=\"hidden\" name=\"colleague_add\"><input type=\"hidden\" name=\"colleague_del\"></form><div id=\"gsc_cods_res\"></div></div></div></div><div data-h=\"800\" class=\"gs_md_wnw gs_md_ds gs_md_wmw\"><div id=\"gs_md_cita-d\" class=\"gs_md_d gs_md_ds gs_ttzi\" role=\"dialog\" tabindex=\"-1\" aria-labelledby=\"gs_md_cita-d-t\" data-cid=\"gs_md_cita-l\" data-wfc=\"gs_md_cita-d-x\"><div class=\"gs_md_hdr\"><a href=\"javascript:void(0)\" id=\"gs_md_cita-d-x\" role=\"button\" aria-label=\"Cancelar\" data-mdx=\"gs_md_cita-d\" class=\"gs_btnCLS gs_md_x gs_md_hdr_c gs_in_ib gs_btn_lrge\"><span class=\"gs_ico\"></span><span class=\"gs_ia_notf\"></span><span class=\"gs_lbl\"></span></a><h2 id=\"gs_md_cita-d-t\" class=\"gs_md_hdr_t\"></h2><div class=\"gs_md_hdr_b\"><button type=\"button\" id=\"gs_md_cita-b-save\" aria-label=\"Guardar\" class=\"gs_btnDNW gs_in_ib gs_btn_act gs_btn_half gs_btn_lsb\"><span class=\"gs_wr\"><span class=\"gs_ico\"></span><span class=\"gs_lbl\"></span></span></button></div></div><div id=\"gs_md_cita-d-bdy\" class=\"gs_md_bdy\"><style>#gs_md_cita-d{width:90%;max-width:1000px;}.gs_el_ph #gs_md_cita-d{width:100%;max-width:none;}#gs_md_cita-d .gs_md_prg{min-height:600px;}</style><div id=\"gs_md_cita-l\" aria-live=\"assertive\"></div></div></div></div><div data-h=\"0\" class=\"gs_md_wnw gs_md_ds gs_md_wmw\"><div id=\"gsc_md_fol\" class=\"gs_md_d gs_md_ds gs_ttzi\" role=\"dialog\" tabindex=\"-1\" aria-labelledby=\"gsc_md_fol-t\" data-wfc=\"gsc_md_fol-x\"><div class=\"gs_md_hdr\"><a href=\"javascript:void(0)\" id=\"gsc_md_fol-x\" role=\"button\" aria-label=\"Cancelar\" data-mdx=\"gsc_md_fol\" class=\"gs_btnCLS gs_md_x gs_md_hdr_c gs_in_ib gs_btn_lrge\"><span class=\"gs_ico\"></span><span class=\"gs_ia_notf\"></span><span class=\"gs_lbl\"></span></a><h2 id=\"gsc_md_fol-t\" class=\"gs_md_hdr_t\">Seguir</h2><div class=\"gs_md_hdr_b\"></div></div><div id=\"gsc_md_fol-bdy\" class=\"gs_md_bdy\"><form method=\"post\" id=\"gsc_fol_f\" action=\"/citations?hl=es&oe=ASCII&user=8ODrYesAAAAJ&view_op=list_works\"><input type=\"hidden\" name=\"xsrf\" value=\"AMD79ooAAAAAY54q86rO4qQg6b3ndDJsMjk1APtyNqLM\"><input type=\"hidden\" name=\"user\" value=\"8ODrYesAAAAJ\"><div id=\"gsc_fol_inp\"></div><div id=\"gsc_fol_cb\"><div class=\"gsc_fol_cr\"><a href=\"javascript:void(0)\" id=\"gsc_fol_a\" role=\"checkbox\" aria-checked=\"false\" data-s=\"0\" class=\"gs_cb_gen gs_in_cb\"><span class=\"gs_lbl\">Nuevos artículos de este autor</span><span class=\"gs_chk\"></span><span class=\"gs_cbx\"></span></a></div><div class=\"gsc_fol_cr\"><a href=\"javascript:void(0)\" id=\"gsc_fol_c\" role=\"checkbox\" aria-checked=\"false\" data-s=\"0\" class=\"gs_cb_gen gs_in_cb\"><span class=\"gs_lbl\">Nuevas citas sobre este autor</span><span class=\"gs_chk\"></span><span class=\"gs_cbx\"></span></a></div><div class=\"gsc_fol_cr\"><a href=\"javascript:void(0)\" id=\"gsc_fol_r\" role=\"checkbox\" aria-checked=\"false\" data-s=\"0\" class=\"gs_cb_gen gs_in_cb\"><span class=\"gs_lbl\">Nuevos artículos relacionados con la investigación de este autor</span><span class=\"gs_chk\"></span><span class=\"gs_cbx\"></span></a></div></div><div id=\"gsc_fol_email\"><label id=\"gsc_fol_ml\" for=\"gsc_fol_m\">Dirección de correo electrónico en la que quieres recibir las notificaciones</label><div class=\"gs_in_txtw 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class=\"gsc_rsb_header\"><span class=\"gsc_rsb_title\">Citado por</span></h3><table id=\"gsc_rsb_st\"><thead><tr><th class=\"gsc_rsb_sth\"></th><th class=\"gsc_rsb_sth\">Total</th><th class=\"gsc_rsb_sth\">Desde 2017</th></tr></thead><tbody><tr><td class=\"gsc_rsb_sc1\"><a href=\"javascript:void(0)\" class=\"gsc_rsb_f gs_ibl\" title=\"Recoge el número de veces que se han citado todas las publicaciones. La segunda columna muestra la versión "actual" de esta estadística, que es el número total de nuevas citas que se han hecho de todas las publicaciones en los últimos 5 años.\">Citas</a></td><td class=\"gsc_rsb_std\">18</td><td class=\"gsc_rsb_std\">18</td></tr><tr><td class=\"gsc_rsb_sc1\"><a href=\"javascript:void(0)\" class=\"gsc_rsb_f gs_ibl\" title=\"Índice h es el mayor número h, de forma que h publicaciones se han citado al menos h veces. La segunda columna muestra la versión "actual" del cálculo, que es el mayor número h, de forma que h publicaciones se han citado al menos h veces más en los últimos 5 años.\">Índice h</a></td><td class=\"gsc_rsb_std\">1</td><td class=\"gsc_rsb_std\">1</td></tr><tr><td class=\"gsc_rsb_sc1\"><a href=\"javascript:void(0)\" class=\"gsc_rsb_f gs_ibl\" title=\"Índice i10 recoge las publicaciones que se han citado al menos diez veces. La segunda columna muestra la versión "actual" de esta estadística, que son las publicaciones que se han citado al menos diez veces más en los últimos 5 años.\">Índice i10</a></td><td class=\"gsc_rsb_std\">1</td><td class=\"gsc_rsb_std\">1</td></tr></tbody></table><style>.gsc_g_t{position:absolute;bottom:0;color:#777;font-size:11px;}.gsc_g_a{position:absolute;bottom:13px;width:15px;background:#777;}.gsc_g_a:hover,.gsc_g_a:focus,.gsc_g_a:active{text-decoration:none;cursor:default;}.gsc_g_al{position:absolute;bottom:15px;left:7px;color:#222;background:white;font-size:11px;padding:1px;border:1px solid #777;border-radius:1px;visibility:hidden;opacity:0;transition:opacity .218s,visibility 0s .218s;}.gsc_g_a:hover .gsc_g_al,.gsc_g_a:focus .gsc_g_al,.gsc_g_a:active .gsc_g_al{visibility:visible;opacity:1;transition:all 0s;}#gsc_md_hist{max-width:250px;}.gsc_md_hist_w{position:relative;overflow:hidden;margin-right:43px;}.gs_md_bdy .gsc_md_hist_w,.gs_el_ph .gsc_md_hist_w,.gs_el_ta .gsc_md_hist_w{overflow-x:auto;padding-bottom:16px;}.gsc_md_hist_b{position:relative;height:174px;width:100%;}.gsc_md_hist_b .gsc_g_a{bottom:auto;}.gsc_md_hist_b .gsc_g_t{bottom:auto;top:161px;}.gsc_md_hist_b:after{position:absolute;right:216px;content:\"\\00A0\";}.gsc_g_hist_x{position:relative;margin-right:45px;}.gsc_g_hist_xl{position:absolute;right:8px;width:35px;}.gs_el_ta .gsc_g_hist_xl,.gs_el_ph .gsc_g_hist_xl{right:16px;}.gsc_g_hist_wrp{padding-top:32px;position:relative;}.gs_el_ta .gsc_g_hist_wrp,.gs_el_ph .gsc_g_hist_wrp{padding-right:8px;}.gs_md_bdy .gsc_g_hist_wrp{border-top:0;}.gs_el_tc .gs_md_bdy .gsc_g_hist_wrp:after,.gs_el_tc.gs_el_ph .gsc_g_hist_wrp:after,.gs_el_tc.gs_el_ta .gsc_g_hist_wrp:after{display:block;content:\"\";position:absolute;z-index:100;top:0;left:0;width:20px;height:100%;background-image:linear-gradient(to left,rgba(255,255,255,0),rgba(255,255,255,1) 80%);}.gsc_g_x,.gsc_g_xt{position:absolute;left:0;border-bottom:1px solid #eee;width:100%;text-align:right;}.gsc_g_x{border-bottom:1px solid #eee;}.gsc_g_xtl{position:absolute;color:#777;}.gsc_g_gtr{position:absolute;}.gsc_g_a:last-child .gsc_g_al{right:0;left:auto;}</style><div class=\"gsc_g_hist_wrp\" dir=\"rtl\"><div class=\"gsc_g_hist_x\"><div class=\"gsc_g_x\" style=\"top:160px;\"></div><div class=\"gsc_g_xt\" style=\"top:0px;\"></div><div class=\"gsc_g_xt\" style=\"top:80px;\"></div></div><div class=\"gsc_g_hist_xl\"><div class=\"gsc_g_xtl\" style=\"top:153px;\">0</div><div class=\"gsc_g_xtl\" style=\"top:-7px;\">8</div><div class=\"gsc_g_xtl\" style=\"top:73px;\">4</div></div><div class=\"gsc_md_hist_w\"><div class=\"gsc_md_hist_b\"><span class=\"gsc_g_t\" style=\"right:163px\">2017</span><span class=\"gsc_g_t\" style=\"right:131px\">2018</span><span class=\"gsc_g_t\" style=\"right:99px\">2019</span><span class=\"gsc_g_t\" style=\"right:67px\">2020</span><span class=\"gsc_g_t\" style=\"right:35px\">2021</span><span class=\"gsc_g_t\" style=\"right:3px\">2022</span><a href=\"javascript:void(0)\" class=\"gsc_g_a\" style=\"right:168px;top:140px;height:20px;z-index:6\"><span class=\"gsc_g_al\">1</span></a><a href=\"javascript:void(0)\" class=\"gsc_g_a\" style=\"right:136px;top:140px;height:20px;z-index:5\"><span class=\"gsc_g_al\">1</span></a><a href=\"javascript:void(0)\" class=\"gsc_g_a\" style=\"right:104px;top:140px;height:20px;z-index:4\"><span class=\"gsc_g_al\">1</span></a><a href=\"javascript:void(0)\" class=\"gsc_g_a\" style=\"right:72px;top:20px;height:140px;z-index:3\"><span class=\"gsc_g_al\">7</span></a><a href=\"javascript:void(0)\" class=\"gsc_g_a\" style=\"right:40px;top:80px;height:80px;z-index:2\"><span class=\"gsc_g_al\">4</span></a><a href=\"javascript:void(0)\" class=\"gsc_g_a\" style=\"right:8px;top:80px;height:80px;z-index:1\"><span class=\"gsc_g_al\">4</span></a></div></div></div></div></div><div class=\"gsc_lcl\" role=\"main\" id=\"gsc_prf_w\"><div id=\"gsc_prf\"><a href=\"javascript:void(0)\" role=\"button\" id=\"gsc_prf_btnf\" class=\"gsc_prf_btn gsc_prf_btn_top gs_btnFA gsc_prf_btn_act\"><span class=\"gs_ico\"></span><span class=\"gsc_prf_btn_lbl\">Seguir</span></a><div id=\"gsc_prf_pu\"><div id=\"gsc_prf_pua\" class=\"gs_rimg\"><style>#gsc_prf_pup-img{width:99px;height:128px;}@media print{#gs_top #gsc_prf_pup-img{width:61pt;height:80pt;}}</style><img alt=\"Jorge Arturo Garza Venegas\" sizes=\"print 61px,99px\" src=\"https://scholar.googleusercontent.com/citations?view_op=view_photo&user=8ODrYesAAAAJ&citpid=1\" id=\"gsc_prf_pup-img\" srcset=\"https://scholar.googleusercontent.com/citations?view_op=view_photo&user=8ODrYesAAAAJ&citpid=1 99w,https://scholar.googleusercontent.com/citations?view_op=medium_photo&user=8ODrYesAAAAJ&citpid=1 199w\"></div></div><div id=\"gsc_prf_i\"><div id=\"gsc_prf_inw\"><div id=\"gsc_prf_in\">Jorge Arturo Garza Venegas</div></div><div class=\"gsc_prf_il\">Tecnologico de Monterrey</div><div class=\"gsc_prf_il\" id=\"gsc_prf_ivh\">Dirección de correo verificada de tec.mx</div><div class=\"gsc_prf_il\" id=\"gsc_prf_int\"><a href=\"/citations?view_op=search_authors&hl=es&oe=ASCII&mauthors=label:statistical_process_monitoring\" class=\"gsc_prf_inta gs_ibl\">Statistical Process Monitoring</a><a href=\"/citations?view_op=search_authors&hl=es&oe=ASCII&mauthors=label:time_series\" class=\"gsc_prf_inta gs_ibl\">Time series</a><a href=\"/citations?view_op=search_authors&hl=es&oe=ASCII&mauthors=label:parametric_methods\" class=\"gsc_prf_inta gs_ibl\">parametric methods</a></div></div></div></div><div id=\"gsc_prf_t_wrp\" role=\"navigation\"><div id=\"gsc_prf_t\" role=\"tablist\"><a id=\"gsc_prf_t-art\" class=\"gsc_prf_tab\" href=\"javascript:void(0)\" role=tab aria-controls=\"gsc_art\" aria-selected=\"true\">Artículos</a><a id=\"gsc_prf_t-cit\" class=\"gsc_prf_tab\" href=\"javascript:void(0)\" role=\"tab\" aria-controls=\"gsc_rsb_cit\">Citado por</a></div></div><div class=\"gsc_lcl gsc_prf_pnl\" id=\"gsc_art\" role=\"region\" 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class=\"gs_icm\"></span></span></button><div id=\"gsc_dd_sort-d\" class=\"gs_md_d gs_md_ds gs_md_ulr\" role=\"menu\" tabindex=\"-1\"><div id=\"gsc_dd_sort-s\" class=\"gs_oph gsc_dd_sec gsc_dd_sep\"><a role=\"menuitem\" href=\"/citations?hl=es&oe=ASCII&user=8ODrYesAAAAJ&view_op=list_works\" tabindex=\"-1\" class=\"gs_md_li gsc_dd_sort-sel\">Ordenar por citas</a><a role=\"menuitem\" href=\"/citations?hl=es&oe=ASCII&user=8ODrYesAAAAJ&view_op=list_works&sortby=pubdate\" tabindex=\"-1\" class=\"gs_md_li\">Ordenar por año</a><a role=\"menuitem\" href=\"/citations?hl=es&oe=ASCII&user=8ODrYesAAAAJ&view_op=list_works&sortby=title\" tabindex=\"-1\" class=\"gs_md_li\">Ordenar por título</a></div></div></div></th><th class=\"gsc_a_c\" scope=\"col\" dir=\"rtl\"><span id=\"gsc_a_ca\"><div class=\"gs_nph\">Citado por</div><div class=\"gs_oph\">Citado por</div></span></th><th class=\"gsc_a_y\" scope=\"col\"><span class=\"gsc_a_h\" id=\"gsc_a_ha\"><a href=\"/citations?hl=es&oe=ASCII&user=8ODrYesAAAAJ&view_op=list_works&sortby=pubdate\" class=\"gsc_a_a\">Año</a></span></th></tr></thead><tbody id=\"gsc_a_b\"><tr class=\"gsc_a_tr\"><td class=\"gsc_a_t\"><a href=\"/citations?view_op=view_citation&hl=es&oe=ASCII&user=8ODrYesAAAAJ&citation_for_view=8ODrYesAAAAJ:u5HHmVD_uO8C\" class=\"gsc_a_at\">Effect of autocorrelation estimators on the performance of the X control chart</a><div class=\"gs_gray\">JA Garza-Venegas, VG Tercero-Gómez, L Lee Ho, P Castagliola, ...</div><div class=\"gs_gray\">Journal of Statistical Computation and Simulation 88 (13), 2612-2630<span class=\"gs_oph\">, 2018</span></div></td><td class=\"gsc_a_c\"><a href=\"https://scholar.google.com.mx/scholar?oi=bibs&hl=es&oe=ASCII&cites=2021578430489910867\" class=\"gsc_a_ac gs_ibl\">17</a></td><td class=\"gsc_a_y\"><span class=\"gsc_a_h gsc_a_hc gs_ibl\">2018</span></td></tr><tr class=\"gsc_a_tr\"><td class=\"gsc_a_t\"><a href=\"/citations?view_op=view_citation&hl=es&oe=ASCII&user=8ODrYesAAAAJ&citation_for_view=8ODrYesAAAAJ:u-x6o8ySG0sC\" class=\"gsc_a_at\">Likelihood ratio test for a change-point in the mean of independent normal observations</a><div class=\"gs_gray\">JA Garza-Venegas</div><div class=\"gs_gray\">IIE Annual Conference. Proceedings, 3152<span class=\"gs_oph\">, 2013</span></div></td><td class=\"gsc_a_c\"><a href=\"https://scholar.google.com.mx/scholar?oi=bibs&hl=es&oe=ASCII&cites=4405980216929272094\" class=\"gsc_a_ac gs_ibl\">1</a></td><td class=\"gsc_a_y\"><span class=\"gsc_a_h gsc_a_hc gs_ibl\">2013</span></td></tr><tr class=\"gsc_a_tr\"><td class=\"gsc_a_t\"><a href=\"/citations?view_op=view_citation&hl=es&oe=ASCII&user=8ODrYesAAAAJ&citation_for_view=8ODrYesAAAAJ:UeHWp8X0CEIC\" class=\"gsc_a_at\">Control charts for autocorrelated processes under parameter estimation</a><div class=\"gs_gray\">JA Garza Venegas</div><div class=\"gs_gray\">Instituto Tecnologico y de Estudios Superiores de Monterrey<span class=\"gs_oph\">, 2018</span></div></td><td class=\"gsc_a_c\"><a href=\"\" class=\"gsc_a_ac gs_ibl\"></a></td><td class=\"gsc_a_y\"><span class=\"gsc_a_h gsc_a_hc gs_ibl\">2018</span></td></tr><tr class=\"gsc_a_tr\"><td class=\"gsc_a_t\"><a href=\"/citations?view_op=view_citation&hl=es&oe=ASCII&user=8ODrYesAAAAJ&citation_for_view=8ODrYesAAAAJ:qjMakFHDy7sC\" class=\"gsc_a_at\">Performance of self-starting control charts for autocorrelated data</a><div class=\"gs_gray\">JA Garza-Venegas, VG Tercero-Gómez, D Barraza-Barraza, ...</div><div class=\"gs_gray\">IIE Annual Conference. Proceedings, 1043-1048<span class=\"gs_oph\">, 2018</span></div></td><td class=\"gsc_a_c\"><a href=\"\" class=\"gsc_a_ac gs_ibl\"></a></td><td class=\"gsc_a_y\"><span class=\"gsc_a_h gsc_a_hc gs_ibl\">2018</span></td></tr><tr class=\"gsc_a_tr\"><td class=\"gsc_a_t\"><a href=\"/citations?view_op=view_citation&hl=es&oe=ASCII&user=8ODrYesAAAAJ&citation_for_view=8ODrYesAAAAJ:9yKSN-GCB0IC\" class=\"gsc_a_at\">An evaluation of change-point estimators for a sequence of normal observations with unknown parameters</a><div class=\"gs_gray\">J Garza-Venegas, V Tercero-Gomez, A Cordero Franco, ...</div><div class=\"gs_gray\">Communications in Statistics-Simulation and Computation 46 (6), 4297-4317<span class=\"gs_oph\">, 2017</span></div></td><td class=\"gsc_a_c\"><a href=\"\" class=\"gsc_a_ac gs_ibl\"></a></td><td class=\"gsc_a_y\"><span class=\"gsc_a_h gsc_a_hc gs_ibl\">2017</span></td></tr><tr class=\"gsc_a_tr\"><td class=\"gsc_a_t\"><a href=\"/citations?view_op=view_citation&hl=es&oe=ASCII&user=8ODrYesAAAAJ&citation_for_view=8ODrYesAAAAJ:d1gkVwhDpl0C\" class=\"gsc_a_at\">Robust change-point estimator for series of normal observations</a><div class=\"gs_gray\">AE Cordero-Franco, JA Garza-Venegas, VG Tercero-Gómez, ...</div><div class=\"gs_gray\">IIE Annual Conference. Proceedings, 2717<span class=\"gs_oph\">, 2014</span></div></td><td class=\"gsc_a_c\"><a href=\"\" class=\"gsc_a_ac gs_ibl\"></a></td><td class=\"gsc_a_y\"><span class=\"gsc_a_h gsc_a_hc gs_ibl\">2014</span></td></tr><tr class=\"gsc_a_tr\"><td class=\"gsc_a_t\"><a href=\"/citations?view_op=view_citation&hl=es&oe=ASCII&user=8ODrYesAAAAJ&citation_for_view=8ODrYesAAAAJ:2osOgNQ5qMEC\" class=\"gsc_a_at\">Analysis of multiple change-points in normally distributed series</a><div class=\"gs_gray\">JA Garza Venegas</div><div class=\"gs_gray\">Universidad Autónoma de Nuevo León<span class=\"gs_oph\">, 2013</span></div></td><td class=\"gsc_a_c\"><a href=\"\" class=\"gsc_a_ac gs_ibl\"></a></td><td class=\"gsc_a_y\"><span class=\"gsc_a_h gsc_a_hc gs_ibl\">2013</span></td></tr></tbody></table><div id=\"gsc_a_sp\"></div><div id=\"gsc_a_err\" class=\"gs_alrt\">El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.</div></div><div id=\"gsc_lwp\"><span id=\"gsc_a_nn\">Artículos 1–7</span><div id=\"gsc_bpf\"><button type=\"button\" id=\"gsc_bpf_more\" disabled class=\"gs_btnPD gs_in_ib gs_btn_flat gs_btn_lrge gs_btn_lsu\"><span class=\"gs_wr\"><span class=\"gs_ico\"></span><span class=\"gs_lbl\">Mostrar más</span></span></button></div></div></form></div></div></div></div><script>var gs_zvb;!function(u){gs_zvb=new Image();gs_zvb.onload=gs_zvb.onerror=function(){gs_zvb=0};gs_zvb.src=u;}(\"https://id.google.com.mx/verify/AL_FIINfIFI0lpT8MSFof6vAAm45_YhBp0f5-w3PClmT6vI1XjtKfOdrmsvZ8kf9mxQ8bRlluY6kPIRBsTikdvb5Vqh76vxDlsMB5VkX9S1GqP6bXk7sXOSPC9KBK9MgG3qmVc3jQ6tSJk0hqg.gif\");</script><noscript><img src=\"https://id.google.com.mx/verify/AL_FIINfIFI0lpT8MSFof6vAAm45_YhBp0f5-w3PClmT6vI1XjtKfOdrmsvZ8kf9mxQ8bRlluY6kPIRBsTikdvb5Vqh76vxDlsMB5VkX9S1GqP6bXk7sXOSPC9KBK9MgG3qmVc3jQ6tSJk0hqg.gif\" width=\"1\" height=\"1\" alt=\"\" style=\"margin:-1px\"></noscript><div id=\"gs_ftr_sp\" role=\"presentation\"></div><div id=\"gs_ftr\" role=\"contentinfo\"><div id=\"gs_ftr_rt\"><a href=\"/intl/es/scholar/about.html\">Ayuda</a><a href=\"//www.google.com.mx/intl/es/policies/privacy/\">Privacidad</a><a href=\"//www.google.com.mx/intl/es/policies/terms/\">Condiciones</a></div></div></div></body></html>"# library(RCurl)
# library(XML)
# url <- "https://scholar.google.com.mx/citations?user=8ODrYesAAAAJ&hl=es"
# html <- htmlTreeParse(url)
# xpathSApply(html, "//title", xmlValue)library(httr)
url <- "https://scholar.google.com.mx/citations?user=8ODrYesAAAAJ&hl=es"
html2 <- GET(url)
content2 <- content(html2, as = "text")
parsedHtml <- htmlParse(content2, asText = TRUE)
xpathSApply(parsedHtml, "//title", xmlValue)## [1] "Jorge Arturo Garza Venegas - Google Académico"# Using handles
google <- handle("http://google.com")
pg1 <- GET(handle = google, path = "/")
pg2 <- GET(handle = google, path = "search")API stands for Application Programming Interfaces.
Remember that:
file opens a connection to a text fileurl opens a connection to a url.gzfile opens a connection to a .gz filebzfile opens a connection to a .bz2 fileOther files can be read from R, usign the foreign
package, which can load data from Minitab, S, SAS, SPSS, Stata, among
others.
The structure of the functions is read.foo. For example,
read.mtp loads a Minitab file.